CN101794371A - Method for adjusting light source threshold value for face recognition - Google Patents
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Abstract
The invention discloses a method for adjusting a light source threshold value for face recognition, which comprises the following steps of: photographing an input image; calculating a first brightness value of the input image; loading a target image; loading a second brightness value of the target image; comparing the first brightness value with the second brightness image to obtain a brightness difference between the input image and the target image; adjusting a basic threshold according to the brightness difference to obtain a recognition threshold; and performing a face recognition process on the input image by using the recognition threshold value.
Description
Technical Field
The present invention relates to a face recognition method, and more particularly, to a method for adjusting a light source threshold for face recognition.
Background
In the face recognition technology, the face of the user can be recognized only within the effective shooting distance of the electronic device with the image extraction function after the electronic device extracts the face image of the user.
Since the face recognition is applied to the electronic device, the face recognition is a result of the electronic device through a series of algorithms and image numerical calculations. The electronic device compares and calculates the input image of the user with the target image in the storage device to obtain a numerical value. The value is used to represent the image similarity value of the user in face recognition. In addition, a basic threshold is set in the electronic device for determining whether the image similarity value passes the recognition criterion in the face recognition procedure.
Generally, the input image of the user extracted by the electronic device is too different from the face image of the actual user due to the difference of the ambient light source. The calculated image similarity value varies too much because the external ambient light source affects the change of the face shadow of the user. The image similarity value cannot meet the standard of the basic threshold value, and the user cannot pass the identification. Therefore, the face recognition procedure of the electronic device is often affected by the ambient light source, so that the recognition effect is reduced and the operation of the user is inconvenient.
Disclosure of Invention
In view of the above problems, the present invention provides a method for adjusting a light source threshold for face recognition, so as to dynamically adjust a basic threshold for face recognition under different environmental light sources.
Therefore, the method for adjusting the light source threshold for face recognition disclosed by the invention comprises the following steps: shooting an input image; calculating a first luminance value of an input image; loading a target image; loading a second brightness value of the target image; comparing the first brightness value with the second brightness value to obtain a brightness difference value between the input image and the target image; adjusting the basic threshold value according to the brightness difference value to obtain an identification threshold value; and performing a face recognition procedure on the input image by using the recognition threshold.
The first luminance value may include a luminance average value and a luminance standard deviation value of the input image, and the second luminance value may include a luminance average value and a luminance standard deviation value of the target image.
In addition, the average value of the luminance of the input image can be calculated using the following equation: <math><mrow><mover><mi>x</mi><mo>‾</mo></mover><mo>=</mo><mfrac><mn>1</mn><mi>N</mi></mfrac><munderover><mrow><mi></mi><mo>∑</mo></mrow><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>N</mi></munderover><msub><mi>x</mi><mi>i</mi></msub><mo>.</mo></mrow></math>
in the calculation formula, the calculation formula is shown,
is the average value of the brightness of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, and xiIs the luminance value of the ith pixel of the input image, and N and i are positive integers.
And, the average brightness value of the target image can be calculated by the following formula: <math><mrow><mover><mi>y</mi><mo>‾</mo></mover><mo>=</mo><mfrac><mn>1</mn><mi>M</mi></mfrac><munderover><mrow><mi></mi><mo>∑</mo></mrow><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>M</mi></munderover><msub><mi>y</mi><mi>j</mi></msub><mo>.</mo></mrow></math>
in the calculation formula, the calculation formula is shown,
is the average value of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, yjIs the brightness value of the jth pixel of the target image, and M and j are positive integers.
In addition, the standard deviation value of the luminance of the input image can be calculated by using the following formula:
in the calculation formula, σ is the standard deviation value of the brightness of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, and xiIs the luminance value of the ith pixel of the input image,
Is the average value of the luminance of the input image, and N and i are positive integers.
And, the standard deviation of the brightness of the target image can be calculated by the following formula:
in the calculation formula, θ is the standard deviation of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, and yjIs the luminance value of the jth pixel of the target image,
Is the average value of the brightness of the target image, and M and j are positive integers.
In addition, before the step of loading the target image and the step of loading the second brightness value of the target image corresponding to the target image, the method may further include: shooting a target image; calculating a second brightness value of the shot target image; and storing the shot target image and the calculated second brightness value.
In addition, the step of comparing the first luminance value with the second luminance value to obtain a luminance difference value between the input image and the target image may include: comparing the brightness average value in the first brightness value with the brightness average value in the second brightness value to obtain a first difference value; comparing the brightness standard difference value of the first brightness value with the brightness standard difference value of the second brightness value to obtain a second difference value; and calculating a brightness difference value between the input image and the target image according to the first difference value and the second difference value.
In addition, the step of adjusting the basic threshold according to the brightness difference value to obtain the identification threshold may include: searching the first lookup table according to the brightness difference value to obtain a first compensation value corresponding to the brightness difference value; searching a second lookup table according to the brightness difference value to obtain a second compensation value corresponding to the brightness difference value; calculating a threshold compensation value according to the first compensation value and the second compensation value; and adjusting the basic threshold value by the threshold compensation value to obtain the identification threshold value.
The step of calculating the compensation threshold value according to the first compensation value and the second compensation value may include: and accumulating the first compensation value and the second compensation value to obtain a compensation threshold value.
Here, the first compensation value relates to a luminance average value of the input image, and the second compensation value relates to a luminance standard deviation value of the input image.
In addition, before the step of adjusting the basic threshold, the method may further include: a basic threshold is set.
Finally, the face recognition procedure may include: detecting a first face block in an input image; detecting a second face region block in the target image; calculating the detected first face area block and the detected second face area block to obtain an image similarity value; and comparing the recognition threshold value with the image similarity value to judge whether the input image passes through the face recognition program.
The method for adjusting the light source threshold value of the face recognition is applied to a face recognition system, and can dynamically adjust the recognition threshold value used in the face recognition under the light sources of different environments. The recognition threshold can be appropriately raised or lowered regardless of poor lighting environments or excessive differences in brightness of images recorded in the database. The user can successfully finish the face identification under different environments and different light rays.
The features and operation of the present invention will now be described in detail with reference to the preferred embodiments illustrated in the drawings.
Drawings
Fig. 1 is a flowchart illustrating a method for adjusting a light source threshold for face recognition according to an embodiment of the invention.
Fig. 2 is a detailed flowchart of a captured target image according to an embodiment of the method for adjusting a light source threshold for face recognition according to the present invention.
Fig. 3 is a detailed flowchart illustrating comparison of brightness differences between an input image and a target image according to an embodiment of the method for adjusting a light source threshold for face recognition of the present invention.
FIG. 4 is a detailed flowchart of an embodiment of adjusting a basic threshold to obtain a recognition threshold in the method for adjusting a light source threshold for face recognition according to the present invention.
FIG. 5 is a detailed flowchart of calculating a compensation threshold according to an embodiment of the method for adjusting a light source threshold for face recognition according to the present invention.
FIG. 6 is a detailed flowchart of a face recognition procedure according to an embodiment of the method for adjusting a light source threshold for face recognition according to the present invention.
Detailed Description
The method for adjusting the light source threshold value for face recognition is applied to an electronic device with an image extraction function. The method can realize the adjustment method of the light source threshold value for face recognition according to the invention by the way that the software or the firmware program is built in the storage device of the electronic device and the processor of the electronic device executes the built-in software or the firmware program and the image extraction function. Here, the electronic device may be a Computer (Computer) having an image extracting function, a Mobile Phone (Mobile Phone) having an image extracting function, a Personal Digital Assistant (PDA) having an image extracting function, or the like, but is not limited to the above electronic devices.
In the present application, the basic threshold is dynamically adjusted to obtain the identification threshold by comparing the brightness difference between the input image and the target image, and then the obtained identification threshold is used to perform the face identification procedure of the input image.
Please refer to fig. 1, which is a flowchart illustrating a method for adjusting a light source threshold for face recognition according to an embodiment of the present invention.
When the electronic device receives the instruction of face recognition, first the electronic device captures an input image (step S110), and calculates a first luminance value of the captured input image (step S120). Then, the electronic device loads the target image from the storage device (step S130), and loads the second luminance value of the target image (step S140). The first luminance value and the second luminance value are compared to obtain a luminance difference value between the input image and the target image (step S150). At this time, the basic threshold is adjusted according to the brightness difference value to obtain the identification threshold (step S160). Finally, a face recognition procedure is performed on the input image using the recognition threshold (step S170).
The first luminance value includes a luminance average value and a luminance standard deviation value of the input image, and the second luminance value includes a luminance average value and a luminance standard deviation value of the target image.
Here, the average value of the luminance of the input image may be calculated using the following equation: <math><mrow><mover><mi>x</mi><mo>‾</mo></mover><mo>=</mo><mfrac><mn>1</mn><mi>N</mi></mfrac><munderover><mrow><mi></mi><mo>∑</mo></mrow><mrow><mi>i</mi><mo>=</mo><mn>1</mn></mrow><mi>N</mi></munderover><msub><mi>x</mi><mi>i</mi></msub><mo>.</mo></mrow></math>
wherein,
is the average value of the brightness of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, and xiIs the luminance value of the ith pixel of the input image, and N and i are positive integers.
And, the average value of the brightness of the target image can be calculated using the following formula: <math><mrow><mover><mi>y</mi><mo>‾</mo></mover><mo>=</mo><mfrac><mn>1</mn><mi>M</mi></mfrac><munderover><mrow><mi></mi><mo>∑</mo></mrow><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>M</mi></munderover><msub><mi>y</mi><mi>j</mi></msub><mo>.</mo></mrow></math>
wherein,
is the average value of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, yjIs the brightness value of the jth pixel of the target image, and M and j are positive integers.
In addition, the luminance standard deviation value of the input image can be calculated using the following formula:
wherein, sigma is the standard deviation value of the brightness of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, and xiIs the luminance value of the ith pixel of the input image,
Is the average value of the luminance of the input image, and N and i are positive integers.
And, the standard deviation value of the brightness of the target image can be calculated by using the following formula:
wherein theta is the brightness standard deviation value of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, and yjIs the luminance value of the jth pixel of the target image,
Is the average value of the brightness of the target image, and M and j are positive integers.
Here, the following implementation steps may be further included before step S130 and step S140.
Referring to fig. 2, first, the electronic device captures a target image (step S210), and calculates a second luminance value of the captured target image (step S220). The electronic device then stores the captured target image and the calculated second luminance value in the storage device (step S230).
Here, the average value of the brightness of the target image may be calculated using the following equation: <math><mrow><mover><mi>y</mi><mo>‾</mo></mover><mo>=</mo><mfrac><mn>1</mn><mi>M</mi></mfrac><munderover><mrow><mi></mi><mo>∑</mo></mrow><mrow><mi>j</mi><mo>=</mo><mn>1</mn></mrow><mi>M</mi></munderover><msub><mi>y</mi><mi>j</mi></msub><mo>.</mo></mrow></math>
wherein,
is the average value of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, yjIs the luminance value of the y-th pixel of the target image, and M and j are positive integers.
And, the standard deviation value of the brightness of the target image can be calculated by using the following formula:
wherein theta is the brightness standard deviation value of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, and yjIs the luminance value of the jth pixel of the target image,
Is the average value of the brightness of the target image, and M and j are positive integers.
Further, the following implementation steps may be included in step S150.
Referring to fig. 3, first, the luminance average value in the first luminance value and the luminance average value in the second luminance value are compared to obtain a first difference value (step S152). Then, the luminance standard deviation value of the first luminance value is compared with the luminance standard deviation value of the second luminance value to obtain a second difference value (step S154). Finally, a brightness difference value between the input image and the target image is calculated according to the first difference value and the second difference value (step S156).
In addition, step S160 may include the following implementation steps.
Referring to fig. 4, first, a first lookup table is looked up according to the luminance difference value to obtain a first compensation value corresponding to the luminance difference value (step S162). Then, the second lookup table is looked up according to the brightness difference value to obtain a second compensation value corresponding to the brightness difference value (step S164). And calculating a threshold compensation value according to the first compensation value and the second compensation value (step S166). Finally, the basic threshold is adjusted by the threshold compensation value to obtain the recognition threshold (step S168).
In one embodiment of the present invention, the first lookup table is a first compensation value corresponding to a first difference value of the luminance difference values. "table two" is a second lookup table according to the embodiment of the present invention, which is a second compensation value corresponding to a second difference value of the luminance difference values.
Watch 1
Watch two
The step S166 may include the following steps.
Referring to fig. 5, the first compensation value and the second compensation value are accumulated to obtain a compensation threshold (step S167).
In addition, the first compensation value is related to a luminance average value of the input image, and the second compensation value is related to a luminance standard deviation value of the input image.
In addition, the electronic device may be preset with a basic threshold for comparing the brightness difference with the input image and the target image during the face recognition procedure.
Finally, step S170 may include the following implementation steps.
Referring to fig. 6, first, a first face block in the input image is detected (step S172). Then, a second face block in the target image is detected (step S174). The detected first face region and the detected second face region are calculated to obtain an image similarity value (step S176). Finally, the recognition threshold is compared with the image similarity value to determine whether the input image passes the face recognition procedure (step S178).
For example, when the electronic device receives an instruction of face recognition, the electronic device first captures an input image and calculates a first brightness value of the captured input image. For convenience of explanation, it is assumed that the average value of the luminance in the first luminance value is 64 and the standard deviation value in the first luminance value is 18. Then, the electronic device loads the target image from the storage device, and loads the second brightness value of the target image. For convenience of explanation, it is assumed that the average value of the luminance in the second luminance value is 86 and the standard deviation value in the second luminance value is 33. The average value 64 of the luminance in the first luminance value is compared with the average value 86 of the luminance in the second luminance value to obtain a first difference value 64-86-22. And comparing the luminance standard deviation value 18 of the first luminance value with the luminance standard deviation value 33 of the second luminance value to obtain a second difference value 18-33-15. Finally, the brightness difference value between the input image and the target image is calculated to be (22, 15) according to the first difference value-22 and the second difference value-15.
According to the first difference value 22 of the luminance difference values (22, 15), the first compensation value corresponding to the luminance difference value is 0.5 of the term 2 by looking up the table one. And, according to the first difference value 15 in the luminance difference value lookup (22, 15), the second compensation value corresponding to the luminance difference value is 3.0 of the item 3 by looking up the "table two". Then, the sum of the first compensation value 0.5 and the second compensation value 3.0 is calculated to obtain the threshold compensation value 3.5. Finally, the basic threshold is adjusted by the threshold compensation value 3.5 to obtain the identification threshold, and then the face identification procedure can be carried out on the input image by utilizing the identification threshold.
In the present embodiment, two input images and a target image having different brightness are described. However, in the practical application of the facial recognition program, a plurality of target images can be loaded into the storage device of the electronic device. The input image is used for respectively carrying out face recognition with a plurality of target images so as to judge whether the input image passes through a face recognition procedure.
The method for adjusting the light source threshold value of the face recognition is applied to a face recognition system, and can dynamically adjust the recognition threshold value used in the face recognition under the light sources of different environments. The recognition threshold can be appropriately raised or lowered regardless of poor lighting environments or excessive differences in brightness of images recorded in the database. The user can successfully finish the face identification under different environments and different light rays.
Although the present invention has been described with reference to the above preferred embodiments, it should be understood that various changes and modifications can be made therein by those skilled in the art without departing from the spirit and scope of the invention.
Claims (15)
1. A method for adjusting a light source threshold value of face recognition comprises the following steps:
shooting an input image;
calculating a first brightness value of the input image;
loading a target image;
loading a second brightness value of the target image;
comparing the first brightness value with the second brightness value to obtain a brightness difference value between the input image and the target image;
adjusting a basic threshold value according to the brightness difference value to obtain an identification threshold value; and
and performing a face recognition procedure on the input image by using the recognition threshold.
2. The method of claim 1, wherein the first luminance value comprises a luminance mean and a luminance standard deviation of the input image, and the second luminance value comprises a luminance mean and a luminance standard deviation of the target image.
3. The method of claim 2, wherein the average brightness value of the input image is calculated by the following formula:
wherein,
is the average brightness value of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, xiIs the luminance value of the ith pixel of the input image, and N and i are positive integers.
4. The method of claim 3, wherein the average brightness value of the target image is calculated by the following formula:
wherein,
is the average brightness value of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, yjIs the brightness value of the jth pixel of the target image, and M and j are positive integers.
5. The method of claim 2, wherein the brightness standard deviation of the input image is calculated by the following formula:
wherein σ is the standard deviation value of the brightness of the input image, N is the total number of pixels of the input image, i is the ith pixel of the input image, and xiIs the luminance value of the i-th pixel of the input image,
Is the average value of the brightness of the input image, and N and i are positive integers.
6. The method of claim 5, wherein the brightness standard deviation of the target image is calculated by the following formula:
wherein θ is the standard deviation of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, and yjIs the brightness value of the jth pixel of the target image,
Is the average value of the brightness of the target image, and M and j are positive integers.
7. The method of claim 1, wherein before the step of loading the target image and before the step of loading the second luminance value of the target image corresponding to the target image, the method further comprises:
shooting the target image;
calculating the second brightness value of the shot target image; and
and storing the shot target image and the calculated second brightness value.
8. The method of claim 7, wherein the average brightness value of the target image is calculated by the following formula:
wherein,
is the average brightness value of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, yjIs the luminance value of the y-th pixel of the target image, and M and j are positive integers.
9. The method of claim 7, wherein the brightness standard deviation of the target image is calculated by the following formula:
wherein θ is the standard deviation of the brightness of the target image, M is the total number of pixels of the target image, j is the jth pixel of the target image, and yjIs the brightness value of the jth pixel of the target image,
Is the average value of the brightness of the target image, and M and j are positive integers.
10. The method of claim 1, wherein the step of comparing the first luminance value with the second luminance value to obtain the luminance difference between the input image and the target image comprises:
comparing a brightness average value in the first brightness value with a brightness average value in the second brightness value to obtain a first difference value;
comparing a brightness standard difference value of the first brightness value with a brightness standard difference value of the second brightness value to obtain a second difference value; and
and calculating the brightness difference value between the input image and the target image according to the first difference value and the second difference value.
11. The method of claim 1, wherein the step of adjusting the basic threshold according to the brightness difference value to obtain the recognition threshold comprises:
searching a first lookup table according to the brightness difference value to obtain a first compensation value corresponding to the brightness difference value;
searching the second lookup table according to the brightness difference value to obtain a second compensation value corresponding to the brightness difference value;
calculating a threshold compensation value according to the first compensation value and the second compensation value; and
the basic threshold is adjusted by the threshold compensation value to obtain the identification threshold.
12. The method of claim 1, wherein the step of calculating the compensation threshold according to the first compensation value and the second compensation value comprises:
the first compensation value and the second compensation value are accumulated to obtain the compensation threshold value.
13. The method of claim 1, wherein the first compensation value is related to a luminance average of the input image and the second compensation value is related to a luminance standard deviation of the input image.
14. The method for adjusting light source threshold of facial recognition as claimed in claim 1, wherein the step of adjusting the basic threshold further comprises:
the basic threshold is set.
15. The method for adjusting light source threshold for facial recognition as claimed in claim 1, wherein the facial recognition procedure comprises:
detecting a first face block in the input image;
detecting a second face block in the target image;
calculating the detected first face block and the detected second face block to obtain an image similarity value; and
comparing the recognition threshold value with the image similarity value to determine whether the input image passes through a face recognition procedure.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102629989A (en) * | 2012-04-01 | 2012-08-08 | 山东神思电子技术股份有限公司 | Environmental irradiation removing photographic method |
| CN103190144A (en) * | 2010-10-27 | 2013-07-03 | 高通股份有限公司 | Region of interest extraction |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1860490A (en) * | 2003-09-30 | 2006-11-08 | 皇家飞利浦电子股份有限公司 | System and method for adaptively setting biometric measurement thresholds |
| CN101103635A (en) * | 2005-01-11 | 2008-01-09 | 伊斯曼柯达公司 | White balance correction in digital camera images |
-
2009
- 2009-02-01 CN CN200910003753A patent/CN101794371A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1860490A (en) * | 2003-09-30 | 2006-11-08 | 皇家飞利浦电子股份有限公司 | System and method for adaptively setting biometric measurement thresholds |
| CN101103635A (en) * | 2005-01-11 | 2008-01-09 | 伊斯曼柯达公司 | White balance correction in digital camera images |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103190144A (en) * | 2010-10-27 | 2013-07-03 | 高通股份有限公司 | Region of interest extraction |
| CN103190144B (en) * | 2010-10-27 | 2016-01-27 | 高通股份有限公司 | Region of interest extracts |
| CN102629989A (en) * | 2012-04-01 | 2012-08-08 | 山东神思电子技术股份有限公司 | Environmental irradiation removing photographic method |
| CN102629989B (en) * | 2012-04-01 | 2014-08-13 | 山东神思电子技术股份有限公司 | Environmental irradiation removing photographic method |
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Application publication date: 20100804 |